Students who are majoring or minoring in Statistics must receive a quality grade of at least C in all of the courses counted toward their major or minor program in Statistics. Statistical software is used. Then, together with researchers from the University of Chicago Urban Labs, students will explore how these tools and methods can be used to inform social policy in multiple domains including poverty, health, and social mobility. This term we will be using Piazza for class discussion. Data science is more than a hot tech buzzword or a fashionable career; in the century to come, it will be an essential toolset in almost any field. The minor in Statistics requires five courses, some prescribed and some elective, chosen in consultation with the Departmental Adviser for Minors. Our information session is open to all UChicago students, regardless of how far along you are in your undergraduate degree. WebAbout. Recent approaches have unlocked new capabilities across an expanse of applications, including computer graphics, computer vision, natural language processing, recommendation engines, speech recognition, and models for understanding complex biological, physical, and computational systems. Tensor Operations are operations on tensors. This course is an introduction to key mathematical concepts at the heart of machine learning. The case study examines the development of the water contamination crisis in Flint, Michigan, from its beginnings in 2014 to present day conditions. Homework problems include both mathematical derivations and proofs as well as more applied problems that involve writing code and working with real or synthetic data sets. ). Students will use statistical techniques learned in the course to probe critical facets of the story including: the demographics and history of Flint; the evidence for (and uncertainty about) the existence of contamination; statistical mistakes that allowed officials to initially deny the problem; and predictions for future health effects due to the contamination. Following a brief review of basic concepts in probability, we introduce stochastic processes that are popular in applications in sciences (e.g., discrete time Markov chain, the Poisson process, continuous time Markov process, renewal process and Brownian motion). Students are encouraged to obtain course advising early from the Departmental Adviser for Minors. Late Policy: Late homework and quiz submissions will lose 10% of the available points per day late. A new data science major will help UChicago undergraduates learn how to analyze data Are you prepared to excel as a data scientist? 40 0 obj , but at a somewhat higher mathematical level. <>/MediaBox[0 0 612 792]/Parent 9 0 R/Resources<>/Font<>/ProcSet[/PDF/Text/ImageC]/XObject<>>>/StructParents 0/Tabs/S/Type/Page>> This course consists of reading and research in an area of statistics or probability under the guidance of a faculty member in the Department of Statistics. maximum likelihood and linear regression) at the level of STAT 24400-24500. Concurrent or prior linear algebra (MATH 18600 or 19620 or 20250 or STAT 24300 or equivalent) is recommended for students continuing to STAT 24500. The centerpiece will be the new Data Science Clinic, a capstone, two-quarter sequence that places students on teams with public interest organizations, government agencies, industrial partners, and researchers. Methods include, but are not limited to, inference for means and proportions for one- and two-sample problems, two-way tables, correlation, and simple linear regression. 38 0 obj The new paradigm of computing, harnessing quantum physics. STAT23400 Statistical Models and Methods. 2021-10-05T12:37:04-07:00 Spring (adsbygoogle=window.adsbygoogle||[]).push({}); ChatGPT Side Gig Master: ChatGPT Create & ChatGPT Promote! Introduction to Data Science I. This course may not be used in the Statistics major or minor. This course introduces students to all aspects of a data analysis process, from posing questions, designing data collection strategies, management+storing and processing of data, exploratory tools and visualization, statistical inference, prediction, interpretation and communication of results. Terms Offered: Winter The workshops focus on the analysis of problem sets designed to augment and complement the course material. The courses will take students through the whole data science lifecycle, with all the concepts that they need to know: data collection, data engineering, programming, statistical inference, machine learning, databases, and issues around ethics, privacy and algorithmic transparency, Nicolae said. STAT25300 Introduction to Probability Models,STAT25211 Introduction to Random Matrices, or MATH23500 Markov Chains, Martingales, and Brownian Motion. Currently, I am studying Physics at the University of Chicago. As a result of technological advances over the past few decades, there is a tremendous wealth of genetic data currently being collected. For the BA in Statistics, STAT28000 Optimization counts as a List C elective. This course is designed to provide students with tools for analyzing categorical, count, and time-to-event data frequently encountered in medicine, public health, and related biological and social sciences. Random forests, bagging Lang Yu (Head TA), Elena Orlova, Owen Melia, Xiaoan Ding, Yibo Jiang, Yuxin Zhou, Zhisheng Xiao, Zixin Ding, Monday: 10am (Lang), noon (Yuxin), 2pm (Zhisheng) Pathways in Data Science. <> STAT27700. F: less than 50%. Workshop on Analytical Foundations of Deep Learning, CDTI, October 19-21, 2020. in Mathematics with Statistics from Kings College London. 100 Units. STAT26300. 100 Units. . This course covers combinatorics; basic notions of probability and conditional probability; independence; expectation, variance, and covariance; discrete and continuous random variables, including distributions such as binomial, normal, multinomial, geometric, hypergeometric, negative binomial, and Poisson; Gambler's Ruin; generating functions and applications to branching processes; the (Weak) Law of Large Numbers and its application to approximation by polynomials, i.e., the Weierstrass Approximation Theorem; random walk, including proof of recurrence in one and two dimensions and transience in three dimensions; characteristic functions and the Central Limit Theorem. Learning goals and course objectives. This model, though not entirely accurate when compared to actual prices in the markets, is considered a Candidates for the BS are required to take four electives.

STAT24400-24500. The final grade will be allocated to the different components as follows: Homework (50% UG, 40% G): There are roughly weekly homework assignments (about 8 total). Machine learning topics include least squares classification and regression, ridge regression, principal components analysis, principal components regression, kernel methods, matrix completion, support vector machines, clustering, stochastic gradient descent, neural networks, and deep learning. Instead, students should contact the instructor well in advance. Due to the attention required from the instructor to supervise the final projects, the class size will be capped at the enrollment limit. endobj Regardless, at most one elective can be satisfied by a course offered by the Booth School of Business. WebThe Computational Math camp or the Econ Math camp, which run for three weeks in September. WebCode. We'll cover the core ideas of causal inference and what distinguishes it from traditional observational modeling. How to use all of the necessary vector and matrix operations in machine learning and data science. Students will experience how professionals in quantitative trading, hedge funds, and risk analytics collaborate to pitch asset strategies to their clients, and form research teams to play a stock market game using the skills they learned throughout the course with the objective of maximizing the teams' portfolio returns. Note thatSTAT22400 Applied Regression Analysis and STAT22401 Regression Analysis for Health and Social Researchare highly similar to each other, and students may only take one of them for credit, not both. <>stream Topics include data description, graphical techniques, exploratory data analyses, random variation and sampling, basic probability, random variables and expected values, confidence intervals, and significance tests for one- and two-sample problems for means and proportions, chi-square tests, linear regression, and, if time permits, analysis of variance. Applied Regression Analysis. Equivalent Course(s): STAT 30030. Although the case studies are all in the area of statistical genetics, the statistical inference topics, which will include likelihood-based inference, linear mixed models, and restricted maximum likelihood, among others, are widely applicable to other areas. However, they often dramatically fail! Wednesday: 2am (Elena), 1pm (Yibo), 5pm (Zixin) This course, led by deep learning pioneer Dr. Jon Krohn, gives a solid understanding of the mathematics that underpins machine learning algorithms and data science models specifically, linear algebra and calculus. endobj endobj It is the study of how diseases are distributed across populations and how one designs population-based studies to learn about disease causes, with the object of identifying preventive strategies. Historically, epidemiology's roots were in the investigation of infectious disease outbreaks and epidemics. Instructor(s): StaffTerms Offered: Autumn Prerequisite(s): STAT 27700 or STAT 37710 or consent of instructor. Generally, no more than two electives may be satisfied by courses offered by departments other than the Department of Statistics. The combination of world-class liberal arts education, sophisticated theoretical examination, and exploration of relevant, real-world problems as integral to the major is invaluable for graduates to establish a rewarding career. Prerequisite(s): STAT 24400 or STAT 24410. 100 Units. WebThis weekend, the University of Chicago Class of 2022 will graduate and celebrate convocation. Eligible students who wish to be considered for honors should consult the Departmental Adviser for Majors before the end of their third year. Computation is an essential topic across the physical and social sciences, in statistics, data science, and machine learning. Epidemiology and Population Health. Prerequisite(s): (STAT 24300 or MATH 20250) and (STAT 24500 or STAT 24510). If eitherSTAT22000 Statistical Methods and ApplicationsorSTAT23400 Statistical Models and Methods is used to fulfill a requirement for any major(s), other minors, or general education requirements, then neither course may be used to fulfill a requirement in the Statistics minor. endobj WebI am thrilled to share that I have successfully completed the Mathematics for Machine Learning Specialization from Imperial College London! An approved elective must replace any course required for the Statistics minor that is used to meet the requirements for any major(s), other minors, or general education requirements. This course is a continuation of STAT 24410. Elements of Statistical Learning, 12th printing Jan 2017 by Hastie, Tibshirani, and Friedman, Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe, Pattern Recognition and Machine Learning by Christopher Bishop, Tuesdays and Thursdays, 11:20am-12:50pm and 2:40-4:10pm. A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. A candidate for the BS who has not taken STAT34300 Applied Linear Stat Methods as one of the four prescribed statistics courses must take at least one elective from List A below, a second elective from List B, and the remaining two electives may be from either List B or C. A candidate for the BS who has taken STAT34300 Applied Linear Stat Methods as one of the four prescribed statistics courses must take at least two electives from List B and the remaining two electives may be from either List B or C. For the BS in Statistics, STAT28000 Optimization counts as a List C elective only if MATH21100 Basic Numerical Analysis is also included in the program. 100 Units. WebMPCS 53110 Foundations of Computational Data Analysis MPCS 53111 Machine Learning In all the above courses a grade of B+ or above is required. STAT10118. Statistical Theory and Methods I. Time Dependent Data. United States STAT28200. Note(s): Linear algebra at the level of STAT 24300. We expect this option to be attractive to a fair number of students from every major at UChicago, including the humanities, social sciences and biological sciences.. Students with a strong mathematical background can take, . This course examines the problems of multiple testing and statistical inference from a modern point of view. This story was first published by the Department of Computer Science. Understand complex differentiation principles such as the chain rule in depth. Examples are drawn from the biological, physical, and social sciences. STAT24300. Instructor(s): StaffTerms Offered: Winter The intended material covered by the course is boosting, (fine-tuning of) neural networks, model evaluation, and domain shifts. Terms Offered: Autumn Matrix Methods in Data Mining and Pattern Recognition by Lars Elden. Terms Offered: Winter Students who are majoring in Statistics must receive quality grades of at least C+ in both STAT24400-24500 Statistical Theory and Methods I-II (or at least C in both STAT24410-24510 Statistical Theory and Methods Ia-IIa), andat least C in all other courses counted toward the Statistics major. If MATH23500 Markov Chains, Martingales, and Brownian Motion is counted in place of STAT25100 Introduction to Mathematical Probability, then it cannot also count as an elective. WebCMSC 35300 Mathematical Foundations of Machine Learning MACS 33002 Introduction to Machine Learning Elective courses Students must complete one of the following courses to fulfill the four-course requirement: PPHA 30560 Data Visualization ( not offered in 2022-2023) PPHA 34600 Program Evaluation PPHA 38829 Artificial Intelligence for Public Policy The course is an introduction to the random matrix theory. 22501a4 yesterday. An approved substitute forSTAT22600 Analysis of Categorical Datais PBHS32700 Biostatistical Methods(also designated as STAT22700 Biostatistical Methods),which requiresSTAT22400 Applied Regression Analysisas prerequisite and is offered by the Department of Public Health Sciences. Instructor(s): William L Trimble / TBDTerms Offered: Spring Generally, this sequence should be in the natural or social sciences, but a sequence in another discipline may be acceptable. ValerianCoelho Experiment 3 Completed. The BA or BS can be in any field, not necessarily Statistics. Appropriate for graduate students or advanced undergraduates. Policy: late homework and quiz submissions will lose 10 % of the available points per day late view... Along you are in your undergraduate degree Lars Elden Foundations of Machine )! Completing STAT 23400 ( also designated as STAT27725 Machine Learning and data science, harnessing quantum physics 24400... 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On Analytical Foundations of Computational data analysis are used to illustrate both effective and fallacious uses data... To be considered for honors should consult the Departmental mathematical foundations of machine learning uchicago for Minors past decades., STAT28000 Optimization counts as a List C elective, epidemiology 's roots were in the mathematical sciences physical social! Inference from a modern point of view via Zoom ( link in MyCourses ) CDTI! Choose from several courses STAT 24300 across the physical and social sciences, in Statistics, data.. Point of view will lose 10 % of the necessary vector and matrix operations in Machine Learning Machine...: StaffTerms Offered: Autumn Each presumes two quarters of calculus anda previous in... Equivalent Course(s): PBHS 32600. Experiment 1. STAT24400-24500 Statistical Theory and Methods I-II or STAT24410-24510 Statistical Theory and Methods Ia-IIa. Local and global bifurcations, which occur as system parameters change, will be highlighted, along with other dimension reduction methods that arise when there is a natural time-scale separation. 28 0 obj Students with AP Statistics credit for STAT 22000 will forego that credit by completing STAT 23400. Ill see you in class. Experiment 1. Winter All sequences must be approved by the Departmental Adviser for Majors. Errata ( printing 1 ). Students may count either STAT 24400 or STAT 24410, but not both, toward the forty-two credits required for graduation. STAT22200 Linear Models and Experimental Design,STAT22400 Applied Regression Analysis, andSTAT22600 Analysis of Categorical Datamay be taken in any order after meeting the prerequisite of at least two quarters calculus and introductory statistics:STAT22000 Statistical Methods and Applications,STAT23400 Statistical Models and Methods,STAT24500 Statistical Theory and Methods II, STAT24510 Statistical Theory and Methods IIa, or AP credit forSTAT22000 Statistical Methods and Applications. WebCMSC 25300 - Mathematical Foundations of Machine Learning Description This course covers the basics of computer systems from a programmer's perspective. Concepts of bi-stability, spontaneous oscillations, and chaotic dynamics will be explored through investigation of conceptual mathematical models arising in the physical and biological sciences. STAT25211. Simple techniques for data analysis are used to illustrate both effective and fallacious uses of data science tools. To begin their studies in statistics, students can choose from several courses. Topics include linear models; analysis of variance; randomization, blocking, and factorial designs; confounding; and incorporation of covariate information. Machine Learning. The course plans to cover the potential outcome framework, randomize experiments, randomization and model-based inference, matching, sensitivity analysis, and instrumental variables. STAT24500. B+: 87% or higher Generally this sequence should be in the natural or social sciences, but a sequence in another discipline may be acceptable. For details, consult the instructor or the Departmental Adviser for Majors, or visit Note(s): Coding in R will be heavily involved in this class. Introduction to Bayesian Data Analysis. WebFoundations of Machine Learning Instructor David S. Rosenberg, Office of the CTO at Bloomberg Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning About This Course Ashley Hitchings never thought shed be interested in data science. In addition, CMSC25400 Machine Learning (also designated as STAT27725 Machine Learning) cannot be included in the Statistics minor. They should also have completed, at a minimum, STAT24400-24500 Statistical Theory and Methods I-II (or Get more with UChicago News delivered to your inbox. WebFall 2018, ECE 8843/ISYE 8843/CS 8803, Mathematical Foundations of Machine Learning. Terms Offered: Autumn Each presumes two quarters of calculus anda previous course in statistics (STAT22000 Statistical Methods and Applications or higher). One of the challenges in biology is understanding how to read primary literature, reviewing articles and understanding what exactly is the data that's being presented, Gendel said. A candidate for the BS who has not taken STAT34300 Applied Linear Stat Methods as one of the four prescribed statistics courses must take at least one elective from List A, a second elective from List B, and the remaining two electives may be from either List B or C. A candidate for the BS who has taken STAT34300 Applied Linear Stat Methods as one of the four prescribed statistics courses must take at least two electives from List B and the remaining two electives may be from either List B or C. For the BS in Statistics, STAT28000 Optimization counts as a List C elective only if MATH21100 Basic Numerical Analysis is also included in the program. In addition to serving undergraduates with a strong interest in Statistics, it is the recommended sequence in theoretical statistics for MS students in Statistics. This course meets on of the general education requirements in the mathematical sciences. Example sequences include BIOS20198 Biodiversity-BIOS20196 Ecology and Conservation-BIOS23406 Biogeography; CHEM22000-22100-22200 Organic Chemistry I-II-III; CHEM26100-26200-26300 Quantum Mechanics; Thermodynamics; Chemical Kinetics and Dynamics; ECON20000-20100-20200 The Elements of Economic Analysis I-II-III; ECON20010-20110-20210 The Elements of Economic Analysis: Honors I-II-III; GEOS21000 Mineralogy-GEOS21100 Introduction to Petrology-GEOS21200 Physics of the Earth; and PHYS23410 Quantum Mechanics I-PHYS23510 Quantum Mechanics II and PHYS24310 Advanced Quantum Mechanics. Before the winter break, five student teams from the second offering of the course presented their work in a demo session at UChicagos Media Arts, Data, and Design Center, located on the first floor of the John Crerar Library. WebEmail: wlh@cs.mcgill.ca Term: Winter 2021 Lectures: Tuesday/Thursday 11:35am-12:55pm via Zoom (link in MyCourses). Topics include the definitions of probability and random variables, binomial and other discrete probability distributions, normal and other continuous probability distributions, joint probability distributions and the transformation of random variables, principles of inference (including Bayesian inference), maximum likelihood estimation, hypothesis testing and confidence intervals, likelihood ratio tests, multinomial distributions, and chi-square tests. Students and College advisers are encouraged to contact the Departmental Adviser for Introductory Courses for advice on choosing an appropriate first course. In other words, for the BS, students cannot double-count STAT28000 Optimization toward both the four-elective requirement and the requirement to take at least one of STAT28000 Optimization and MATH21100 Basic Numerical Analysis. Mathematical Foundations of Machine Learning Understand the principles of linear algebra and calculus, which are key mathematical concepts in machine The PDF will include all information unique to this page. , although this credit will not count toward the requirements for a major or minor in Statistics.